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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A Review of Crystalline Silicon Bifacial Photovoltaic Performance Characterisation and Simulation

Bifacial photovoltaic (PV) technology has received considerable attention in recent years due to the potential to achieve higher annual energy yield compared to its monofacial counterpart. Higher annual energy yield is a crucial factor (even more than to further reduce the module costs) because, with the use of higher power PV modules, the high BOS (Balance of System) costs can be reduced, resulting in the lowest LCOE (levelised cost of energy). The International Technology Roadmap for Photovoltaic (ITRPV) predicts an upward trend for the shares of crystalline silicon (c-Si) bifacial PV cells and modules in the global PV market in the next decade, i.e., more than 35% in 2028. Two key enabling factors have been identified to promote the widespread use of c-Si bifacial PV devices, namely the bifacial PV performance measurement method/standard for indoor characterisation and comprehensive simulation models for outdoor performance characterisation. Both will increase the bankability of bifacial PV technology. In this paper, a comprehensive review of the state-of-the-art of the c-Si bifacial PV performance characterisation and simulation is presented. First, an overview of the indoor characterisation of c-Si bifacial PV cells and modules is presented, followed by an overview of the outdoor characterisation of c-Si bifacial PV modules and the draft technical specification, IEC TS 60904-1-2. The second part of this paper reviews the current status of bifacial PV performance modelling, which includes the three primary sub-models: optical, electrical, and thermal models. This paper also provides an overview of the required future research to address the challenges associated with the characterisation and simulation of c-Si bifacial PV devices.

14 SOLAR ENERGY↗
DOE OSTI2018

Systematic Parameterization of Lignin for the CHARMM Force Field

Lignin is an abundant aromatic biopolymer within plant cell walls formed through radical coupling chemistry, whose composition and topology can vary greatly depending on the biomass source. Computational modeling provides a complementary approach to traditional experimental techniques to probe lignin interactions, lignin structure, and lignin material properties. However, current modeling approaches are limited based on the subset of lignin chemistries covered by existing lignin force fields. To fill the gap, we developed a comprehensive lignin force field that accounts for more lignin-lignin and lignin-carbohydrate interlinkages than existing lignin force fields, and also greatly expands the lignin monomer chemistries that can be modeled beyond simple alcohols and into the rich mixture of natural lignin varieties. The development of this force field utilizes recent developments in parameterization methodology, and synthesizes them into a workflow that combines target data from multiple molecules simultaneously into a single consistent and comprehensive parameter set. The parameter set represents a significant improvement to alternatives for atomic modeling of diverse lignin topologies, more accurately reproducing experimental observables while also significantly reducing the error relative to quantum calculations. The improved energetics, as well as the rigid adherence to CHARMM parameterization philosophy, enables simulation of lignin within its biological context with greater accuracy than was previously possible. The lignin force field presented here is therefore a crucial first step towards modeling lignin structure across a broad range of environments, including within plant cell walls where lignin is complexed with carbohydrates and deconstructed by bacterial or fungal enzymes, or as it exists within industrial solvent mixtures. Future simulations enabled by this updated lignin force field will thus lead to better chemical and structural understanding of lignin, providing new insight into its role in biomass recalcitrance or probing the potential for lignin to be used within industrial processes.

09 BIOMASS FUELS↗
DOE OSTI2020

Functional metal–organic frameworks as effective sensors of gases and volatile compounds

Developing efficient sensor materials with superior performance for selective, fast and sensitive detection of gases and volatile organic compounds (VOCs) is essential for human health and environmental protection, through monitoring indoor and outdoor air pollutions, managing industrial processes, controlling food quality and assisting early diagnosis of diseases. Metal–organic frameworks (MOFs) are a unique type of crystalline and porous solid material constructed from metal nodes (metal ions or clusters) and functional organic ligands. They have been investigated extensively for possible use as high performance sensors for the detection of many different gases and VOCs in recent years, due to their large surface area, tunable pore size, functionalizable sites and intriguing properties, such as electrical conductivity, magnetism, ferroelectricity, luminescence and chromism. The high porosity of MOFs allows them to interact strongly with various analytes, including gases and VOCs, thus resulting in easily measurable responses to different physicochemical parameters. Although much of the recent work on MOF-based luminescent sensors have been summarized in several excellent reviews (up to 2018), a comprehensive overview of these materials for sensing gases and VOCs based on chemiresistive, magnetic, ferroelectric, and colorimertic mechanisms is missing. In this review, we highlight the most recent progress in developing MOF sensing and switching materials with an emphasis on sensing mechanisms based on electricity, magnetism, ferroelectricity and chromism. We provide a comprehensive analysis on the MOF–analyte interactions in these processes, which play a key role in the sensing performance of the MOF-based sensors and switches. We discuss in detail possible applications of MOF-based sensing and switching materials in detecting oxygen, water vapor, toxic industrial gases (such as hydrogen sulfide, ammonia, sulfur dioxide, nitrous oxide, carbon oxides and carbon disulfide) and VOCs (such as aromatic and aliphatic hydrocarbons, ketones, alcohols, aldehydes, chlorinated hydrocarbons and N,N'-dimethylformamide). Altogether, this review serves as a timely source of information and provides insight for the future development of advanced MOF materials as next-generation gas and VOC sensors.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Atomically dispersed metal–nitrogen–carbon catalysts for fuel cells: advances in catalyst design, electrode performance, and durability improvement

The urgent need to address the high-cost issue of proton-exchange membrane fuel cell (PEMFC) technologies, particularly for transportation applications, drives the development of simultaneously highly active and durable platinum group metal-free (PGM-free) catalysts and electrodes. The past decade has witnessed remarkable progress in exploring PGM-free cathode catalysts for the oxygen reduction reaction (ORR) to overcome sluggish kinetics and catalyst instability in acids. Among others, scientists have identified the newly emerging atomically dispersed transition metal (M: Fe, Co, or/and Mn) and nitrogen co-doped carbon (M–N–C) catalysts as the most promising alternative to PGM catalysts. Here, we provide a comprehensive review of significant breakthroughs, remaining challenges, and perspectives regarding the M–N–C catalysts in terms of catalyst activity, stability, and membrane electrode assembly (MEA) performance. A variety of novel synthetic strategies demonstrated effectiveness in improving intrinsic activity, increasing active site density, and attaining optimal porous structures of catalysts. Rationally designing and engineering the coordination environment of single metal MN x sites and their local structures are crucial for enhancing intrinsic activity. Increasing the site density relies on the innovative strategies of restricting the migration and agglomeration of single metal sites into metallic clusters. Relevant understandings provide the correlations among the nature of active sites, nanostructures, and catalytic activity of M–N–C catalysts at the atomic scale through a combination of experimentation and theory. Current knowledge of the transferring catalytic properties of M–N–C catalysts to MEA performance is limited. Rationally designing morphologic features of M–N–C catalysts play a vital role in boosting electrode performance through exposing more accessible active sites, realizing uniform ionomer distribution, and facilitating mass/proton transports. We outline future research directions concerning the comprehensive evaluation of M–N–C catalysts in MEAs. The most considerable challenge of current M–N–C catalysts is the unsatisfied stability and rapid performance degradation in MEAs. Therefore, we further discuss practical methods and strategies to mitigate catalyst and electrode degradation, which is fundamentally essential to make M–N–C catalysts viable in PEMFC technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Plasmonic nanorod probes’ journey inside plant cells for in vivo SERS sensing and multimodal imaging

Nanoparticle-based platforms are gaining strong interest in plant biology and bioenergy research to monitor and control biological processes in whole plants. However, in vivo monitoring of biomolecules using nanoparticles inside plant cells remains challenging due to the impenetrability of the plant cell wall to nanoparticles beyond the exclusion limits (5-20 nm). To overcome this physical barrier, we have designed unique bimetallic silver-coated gold nanorods (AuNR@Ag) capable of entering plant cells, while conserving key plasmonic properties in the near-infrared (NIR). To demonstrate cellular internalization and tracking of the nanorods inside plant tissue, we used a comprehensive multimodal imaging approach that included transmission electron microscopy (TEM), confocal fluorescence microscopy, two-photon luminescence (TPL), X-ray fluorescence microscopy (XRF), and photoacoustics imaging (PAI). We successfully acquired SERS signals of nanorods in vivo inside plant cells of tobacco leaves. On the same leaf samples, we applied orthogonal imaging methods, TPL and PAI techniques for in vivo imaging of the nanorods. This study first demonstrates the intracellular internalization of AuNR@Ag inside whole plant systems for in vivo SERS analysis in tobacco cells. This work demonstrates the potential of this nanoplatform as a new nanotool for intracellular in vivo biosensing for plant biology.

Cupil-Garcia, Vanessa↗
DOE OSTI2022

Experimental-based mechanistic study and optimization of hydrothermal liquefaction of anaerobic digestates

Valorization of agricultural and food waste digestates is crucial for sustainable waste management to reduce environmental impacts and improve the economics of commercial farms. Hydrothermal liquefaction (HTL) of anaerobic digestates was evaluated to recover resources by converting them into carbon-dense biocrude oil and a nutrient-rich HTL aqueous phase (HTL-AP) coproduct. The effects of HTL temperature (280–360 °C), reaction time (10–50 min), feedstock pH (2.5–8.5), digestate salt content (1–5 wt%), and digestate cellulose-to-lignin ratio (0.2–1.8) on energy and nutrient recovery were systematically investigated in a set of well-designed experiments following a half-fractional central composite protocol. Response surface analysis combined with HTL product characterization and comparative literature study produced a comprehensive reaction pathway for HTL of anaerobic digestates. Moreover, this analysis revealed the importance of acidic feedstocks (pH 3.00–5.53), high reaction temperatures (337–360 °C), and reaction times <45 or 45–50 min for digestates with Cel/Lig >1 or <1, for maximizing the energy recovered in biocrude (high carbon yield and low heteroatom content) and the amounts of P, NH 3 –N, and Mg distributed in the HTL-AP. Acidic conditions catalyzed biocrude production, inhibited the Maillard reaction (lowering the nitrogen content in biocrude), and partitioned nutrients into the HTL-AP. Higher reaction temperatures coupled with longer reaction times activated hydro-denitrogenation and deoxygenation reactions to improve biocrude quality. Finally, this work provides not only validated methods to achieve targeted resource recovery for specific feedstock compositions using HTL, but also a comprehensive mechanistic understanding of the HTL of biomass waste for controlling target product characteristics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Synergistic effect of polyaniline on stabilizing Pt nanoparticles in PEMFCs†

The stability of Pt nanoparticles on a carbon support is crucial for the lifespan of polymer electrolyte membrane fuel cells as well as other electrocatalysis systems such as electrolyzers. Here we took the approach of utilizing the covalently grafted polyaniline on carbon to stabilize Pt nanoparticles by simultaneously alleviating the particle migration and mitigating the Ostwald ripening, which are two major mechanisms for loss of the catalyst stability. A comprehensive investigation of the stability and performance of Pt catalyst nanoparticles on these supports reveals that the polyaniline can shift the Pt L edge binding energy and the Pt 4f peak energy, leading to the increased redox potential of the Pt nanoparticles and making them more resistant to oxidation. Interestingly, the highest polyaniline density (50 wt%) does not show the best catalyst stability, rather, the second (33 wt%) demonstrates the best catalyst stability among these catalysts. Combining the XPS, XAS and fuel cell stability studies, we concluded that the locations of the Pt nanoparticles over the polyaniline layer on the carbon surface depend on the surface density of the polyaniline over the carbon surface. The Pt nanoparticles in the 50 wt% polyaniline catalyst are wrapped by the polyaniline polymer but do not sit directly on the carbon surface, while Pt nanoparticles in the 33 wt% polyaniline catalyst sit on the carbon surface and are densely surrounded by the polyaniline polymer. The results show that the mass activity loss is 12.5% while the ECSA (electrochemically active surface area) loss is 37.1% after 30k cycles of accelerating stress test for the 33 wt% polyaniline catalyst, far exceeding the DOE 2020 target for MEA (i.e., mass activity loss < 50%, and ECSA loss < 40%). Overall, the polyaniline has a synergistic effect on mitigating the surface migration and slowing down the Ostwald ripening to stabilize the Pt nanoparticles in fuel cells. The novel strategy to stabilize Pt nanoparticles using polyaniline opens a new pathway in the development of highly stable catalysts: relying on the functionalization group on the carbon support, instead of just focusing on the catalyst itself.

Li, Chenzhao↗
DOE OSTI2023

The nature and suppression strategies of interfacial reactions in all-solid-state batteries

Solid-state Li batteries are promising energy storage devices owing to their high safety and high theoretical energy density. However, the serious interfacial reaction between solid state electrolytes and cathodes deteriorates the battery performance, impeding the realization of long-term cyclability. The buried nature of the interphase layer presents a significant challenge in achieving a comprehensive understanding of the underlying interfacial reaction mechanisms. Herein, we systematically explore the interfacial reaction evolutions and interphase compositions and electronic properties between the popular oxide cathodes and sulfide solid electrolytes (SSEs). This includes analysis of the chemical and electrochemical reactions between cathodes/coatings and SSEs, as well as the electrochemical self-decomposition of SSEs by thermodynamic phase equilibrium analysis. Herein, we disclose that the driving force of the electrochemical reaction at the chemical potential of μ Li is much stronger than that of the chemical reaction, which dominates the interfacial reaction. Preventing the formation of an electronically conductive interphase is crucial in inhibiting the continuous interfacial degradation during long-term cycling, which can be achieved through the optimized combination of cathodes and SSEs, as well as the introduction of functional coatings between them. Based on these findings, the percentage of molar fraction ( f ) of electronically conductive species in the formed interphase is proposed as a key factor for indicating the interfacial stability for the first time. Furthermore, we propose a specific high-throughput screening scheme to filter the functional coating materials by comprehensively evaluating their functionality. The tiered screening identifies 48 coating materials with optimal properties. The work highlights the significant roles of rational coupling of the cathodes and SSEs, and optimizing interfacial coating materials for solid-state batteries. It opens new avenues for engineering an interphase with improved interfacial compatibility to realize long-term cyclability.

25 ENERGY STORAGE↗
DOE OSTI2024

Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation

Machine learning (ML) is rapidly emerging as a pivotal tool in the hydrogen energy industry for the creation and optimization of electrocatalysts, which enhance key electrochemical reactions like the hydrogen evolution reaction (HER), the oxygen evolution reaction (OER), the hydrogen oxidation reaction (HOR), and the oxygen reduction reaction (ORR). This comprehensive review demonstrates how cutting-edge ML techniques are being leveraged in electrocatalyst design to overcome the time-consuming limitations of traditional approaches. ML methods, using experimental data from high-throughput experiments and computational data from simulations such as density functional theory (DFT), readily identify complex correlations between electrocatalyst performance and key material descriptors. Leveraging its unparalleled speed and accuracy, ML has facilitated the discovery of novel candidates and the improvement of known products through its pattern recognition capabilities. This review aims to provide a tailored breakdown of ML applications in a format that is readily accessible to materials scientists. Hence, we comprehensively organize ML-driven research by commonly studied material types for different electrochemical reactions to illustrate how ML adeptly navigates the complex landscape of descriptors for these scenarios. We further highlight ML's critical role in the future discovery and development of electrocatalysts for hydrogen energy transformation. Potential challenges and gaps to fill within this focused domain are also discussed. As a practical guide, we hope this work will bridge the gap between communities and encourage novel paradigms in electrocatalysis research, aiming for more effective and sustainable energy solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Mechanistic insight into the effects of A-site doping in perovskite nanorods on interfacial Li-ion and Na-ion transport in polymer–perovskite composite electrolytes

Composite polymer electrolytes (CPEs) offer a promising pathway to safer and higher energy density electrochemical energy storage yet optimizing interfacial ion transport remains a critical challenge due to high resistances and a lack of understanding of the complex interfacial electrostatic interactions. This work investigates the mechanistic origins of the interfacial ion transport enhancement in single-ion conducting (SIC) polymer electrolytes filled with A-site disordered perovskite LaxMyTiOz (LMTO) (M = Li, Na, K) nanorods. By integrating Density Functional Theory (DFT) with broadband dielectric spectroscopy (BDS) and pulsed-field-gradient NMR (PFG-NMR), we analyze the ion transport behavior in Li-based and Na-based SIC systems containing compositionally distinct LMTO fillers (LMTO800 and LMTO900). Specifically, we introduce the site-to-site energy difference (ΔE) descriptor, which extends beyond single-site descriptors such as adsorption energy and ion binding energies. We demonstrate that ΔE together with ion binding energies provide a more comprehensive picture of the energy landscape at the polymer–ceramic interface. The combined DFT and experimental results show that A-site doping in the ceramic filler can effectively modulate ΔE and ion binding energies, creating a favorable potential energy landscape that promotes enhanced ion transport along the interface. This comprehensive study illustrates the impact of ceramic compositional tuning on interfacial ion transport and provides materials design rules towards real-world applications.

B shepard, Lauren [Pennsylvania State University]↗
DOE OSTI2024

A graph embedding‐based approach for automatic cyber‐physical power system risk assessment to prevent and mitigate threats at scale

Abstract Power systems are facing an increasing number of cyber incidents, potentially leading to damaging consequences to both physical and cyber aspects. However, the development of analytical methods for the study of large‐scale power infrastructures as cyber‐physical systems is still in its early stages. Drawing inspiration from machine‐learning techniques, the authors introduce a method inspired by the principles of graph embedding that is tailored for quantitative risk assessment and the exploration of possible mitigation strategies of large‐scale cyber‐physical power systems. The primary advantage of the graph embedding approach lies in its ability to generate numerous random walks on a graph, simulating potential access paths. Meanwhile, it enables capturing high‐dimensional structures in low‐dimensional spaces, facilitating advanced machine‐learning applications, and ensuring scalability and adaptability for comprehensive network analysis. By employing this graph embedding‐based approach, the authors present a structured and methodical framework for risk assessment in cyber‐physical systems. The proposed graph embedding‐based risk analysis framework aims to provide a more insightful perspective on cyber‐physical risk assessment and situation awareness for power systems. To validate and demonstrate its applicability, the method has been tested on two cyber‐physical power system models: the Western System Coordinating Council (WSCC) 9‐Bus System and the Illinois 200‐Bus System , thereby showing its advantages in enhancing the accuracy of risk analysis and comprehensiveness of situational awareness.

Sun, Shining↗
DOE OSTI2023

Condition monitoring of permanent magnet AC machines for all-electric transportation systems: State of the art

The current state of the art on emerging and efficient techniques for condition monitoring of permanent magnet (PM) alternating-current (AC) machines deployed in electric vehicle (EV) applications is presented. The discussion includes the most common and specific types of faults in PM motors, such as rotor demagnetisation and stator inter-turn faults, respectively. Fault indicators, such as voltage (v s ) and current (i s ) signals and machine signatures based on motor back electromotive force (EMF) (E B ) and magnetic flux (φ), are taken into account as a measuring quantity in diagnosing motor faults. Other signatures, including thermal analysis, acoustic noise, and vibrations, are also illustrated as some of the emerging techniques in estimating the performance of EV motors while under operations. In addition, various fault modelling methods, condition monitoring techniques, and comprehensive approaches applied in diagnosing the effect of machine faults during its incipient stages are illustrated. Since most of the fault diagnostic techniques discussed here include only machine-based quantities as fault indices/indicators, the provided solutions are therefore found to be more reliable and accurate for diagnosing the motor faults. This comprehensive review study is inclusive of the existing fault diagnostic techniques, which are currently employed in industrial and commercial practices, in addition to the new methodologies proposed by the authors. All the given condition monitoring schemes therefore seem significantly vital in estimating the state of health of PM AC machines while under operation in all-electric transportation systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Experimental spectrum averaged cross sections (SACS) in 252 Cf(sf) neutron field and its impact on the evaluation of neutron standards

A new evaluation of spectrum averaged cross sections (SACS) of 235 U, 238 U, and 239 Pu measured in the 252 Cf(sf) reference neutron field is presented and found to be consistent with the original Mannhart SACS evaluation in IRDF-2002. The comprehensive vetted experimental database that includes SACS ratio and absolute SACS measurements of major actinides is being used to update the SACS database employed as input of the new GMApy code to derive the Neutron Standards. An update of the current neutron standards based on Time Projection Chamber (TPC) shape data, a new comprehensive uncertainty quantification, and revised SACS experimental database is proposed which result in a 0.7% increase of the evaluated 239 Pu(n,f)/ 235 U(n,f) crosssection ratio in the 1–5 MeV energy region. The increase is due to a 0.3% reduction of the standard 235 U(n,f) cross section and a 0.4% increase of the 239 Pu(n,f) reference cross section in the 1–5 MeV energy region. Those changes are well within estimated USU fission cross-section uncertainties of 1.2%, but are relevant for the evaluated mean values.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Improved value for the silicon free exciton binding energy

The free exciton binding energy is a key parameter in silicon material and device physics. In particular, it provides the necessary link between the energy threshold for valence to conduction band optical absorption and the bandgap determining electronic properties. The long accepted low temperature binding energy value of 14.7 ± 0.4 meV is reassessed taking advantage of developments subsequent to its original determination, leading to the conclusion that this value is definitely an underestimate. Using three largely independent experimental data sets, an improved low temperature value of 15.01 ± 0.06 meV is deduced, in good agreement with the most comprehensive theoretical calculations to date.

36 MATERIALS SCIENCE↗
DOE OSTI2013

The thermodynamic properties of hydrated γ-Al{sub 2}O{sub 3} nanoparticles

In this paper we report a combined calorimetric and inelastic neutron scattering (INS) study of hydrated γ-Al{sub 2}O{sub 3} (γ-alumina) nanoparticles. These complementary techniques have enabled a comprehensive evaluation of the thermodynamic properties of this technological and industrially important metal oxide to be achieved. The isobaric heat capacity (C{sub p}) data presented herein provide further critical insights into the much-debated chemical composition of γ-alumina nanoparticles. Furthermore, the isochoric heat capacity (C{sub v}) of the surface water, which is so essential to the stability of all metal-oxides at the nanoscale, has been extracted from the high-resolution INS data and differs significantly from that of ice‑Ih due to the dominating influence of strong surface-water interactions. This study also encompassed the analysis of four γ-alumina samples with differing pore diameters [4.5 (1), 13.8 (2), 17.9 (3), and 27.2 nm (4)], and the results obtained allow us to unambiguously conclude that the water content and pore size have no influence on the thermodynamic behaviour of hydrated γ-alumina nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Defect interactions with stepped CeO{sub 2}/SrTiO{sub 3} interfaces: Implications for radiation damage evolution and fast ion conduction

Due to reduced dimensions and increased interfacial content, nanocomposite oxides offer improved functionalities in a wide variety of advanced technological applications, including their potential use as radiation tolerant materials. To better understand the role of interface structures in influencing the radiation damage tolerance of oxides, we have conducted atomistic calculations to elucidate the behavior of radiation-induced point defects (vacancies and interstitials) at interface steps in a model CeO{sub 2}/SrTiO{sub 3} system. We find that atomic-scale steps at the interface have substantial influence on the defect behavior, which ultimately dictate the material performance in hostile irradiation environments. Distinctive steps react dissimilarly to cation and anion defects, effectively becoming biased sinks for different types of defects. Steps also attract cation interstitials, leaving behind an excess of immobile vacancies. Further, defects introduce significant structural and chemical distortions primarily at the steps. These two factors are plausible origins for the enhanced amorphization at steps seen in our recent experiments. The present work indicates that comprehensive examination of the interaction of radiation-induced point defects with the atomic-scale topology and defect structure of heterointerfaces is essential to evaluate the radiation tolerance of nanocomposites. Finally, our results have implications for other applications, such as fast ion conduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗